Advertisement

Application of Artificial Intelligence-Based Techniques in Controlling the STATCOM Used for Compensation for Voltage Dips in DFIG-Based Grid-Connected Wind Power System

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 435)

Abstract

Severe voltage sag in weak power systems connected to DFIG-based wind farms may lead to voltage instability. In such cases, FACTS devices like static synchronous compensator (STATCOM) can provide voltage support at the point of common coupling (PCC) by dynamic injection of reactive power. In this research attempt, three artificial intelligence-based techniques have been used to control the STATCOM—fuzzy logic, particle swarm optimization (PSO) and a combination of fuzzy logic and PSO. The STATCOM, controlled by the three proposed techniques—fuzzy-PI, PSO-PI and fuzzy PSO-PI, provides voltage compensation in the DFIG-based grid-connected wind power system in five test cases, namely simultaneous occurrence of step change (drop) in wind speed and dip in grid voltage, single-line-to-ground (SLG) fault, line-to-line (LL) fault, double-line-to-ground (DLG) fault and sudden increase in load by more than a thousand times. A performance comparison regarding the amount of voltage compensation offered is done among all the three artificial intelligence-based STATCOM control techniques in all the five test cases.

Keywords

Static synchronous compensator (STATCOM) Fuzzy logic Particle swarm optimization (PSO) Grid-connected Point of common coupling (PCC) Doubly fed induction generator (DFIG) 

References

  1. 1.
    Ahuja, H., Bhuvaneswari, G., Balasubramanian, R.: Performance comparison of DFIG and PMSG based WECS. In: IET Conference on Renewable Power Generation (2011)Google Scholar
  2. 2.
    Qiao, W., Venayagamoorthy, G.K., Harley, R.G.: Real-time implementation of a STATCOM on a wind farm equipped with doubly fed induction generators. IEEE Trans. Ind. Appl. 45(1), 98–107 (2009)Google Scholar
  3. 3.
    Qiao, W., Venayagamoorthy, G.K., Harley, R.G.: Coordinated reactive power control of large wind farm and a STATCOM using heuristic dynamic programming. IEEE Trans. Energy Convers. 24(2), 493–503 (2009)Google Scholar
  4. 4.
    Luo, A., Tang, C., Shuai, Z., Tang, J., Xu, X.Y., Chen, D.: Fuzzy-PI-based direct-output-voltage control strategy for the STATCOM used in utility distribution systems. IEEE Trans. Ind. Electron. 56(7) (2009)Google Scholar
  5. 5.
    Chauhan, S., Chopra, V., Singh, S.: Power system transient stability improvement using fuzzy PI based STATCOM controller. In: 2nd International Conference on Power, Control and Embedded Systems (2012)Google Scholar
  6. 6.
    Ghafouri, A., Zolghadri, M.R., Ehsan, M., Elmatboly, O., Homaifar, A.: Fuzzy controlled STATCOM for improving power system transient stability. In: Power Symposium, NAPS, IEEE Conference Publications (2007)Google Scholar
  7. 7.
    Gaing, Z.-L.: A particle swarm optimization approach for optimum design of PID controller in AVR system. IEEE Trans. Energy Convers. 19(2) (2004)Google Scholar
  8. 8.
    Liu, C.-H., Hsu, Y.-Y.: Design of a self-tuning PI controller for a STATCOM using particle swarm optimization. IEEE Trans. Ind. Electron. 57(2) (2010)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.National Institute of TechnologyPatnaIndia

Personalised recommendations